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HHV Predicting Correlations for Torrefied Biomass Using Proximate and Ultimate Analyses.

Daya Ram Nhuchhen1, Muhammad T Afzal2

  • 1Mechanical Engineering Department, University of New Brunswick, Fredericton, NB E3B 5A3, Canada. daya.nhuchhen@unb.ca.

Bioengineering (Basel, Switzerland)
|September 28, 2017
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Summary

Existing correlations inaccurately predict the higher heating value (HHV) of torrefied biomass due to significant fuel characteristic changes. New, validated correlations were developed for improved accuracy in thermochemical process modeling.

Keywords:
biomasscorrelationshigher heating valueproximate analysistorrefactionultimate analysis

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Area of Science:

  • Biomass energy conversion
  • Thermochemical process modeling
  • Renewable energy research

Background:

  • Existing correlations predict raw biomass higher heating value (HHV) using proximate and ultimate analyses.
  • Biomass torrefaction significantly alters fuel characteristics, potentially invalidating existing HHV prediction models.

Purpose of the Study:

  • To evaluate the suitability of existing HHV correlations for torrefied biomass.
  • To develop new, accurate correlations for predicting the HHV of torrefied biomass.

Main Methods:

  • Tested existing HHV prediction correlations with torrefied biomass data.
  • Developed new HHV prediction correlations using torrefied biomass data.
  • Validated new correlations using an independent dataset of 26 samples.

Main Results:

  • Existing correlations exhibited high estimation errors for torrefied biomass.
  • New correlations demonstrated good predictive accuracy after validation.
  • Selected correlations incorporated all proximate and ultimate analysis components with minimal errors.

Conclusions:

  • Existing HHV correlations are unsuitable for torrefied biomass.
  • Newly developed correlations provide accurate HHV prediction for torrefied biomass.
  • These new correlations are valuable for modeling thermochemical processes involving torrefied biomass.